{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:39.206251Z",
     "start_time": "2025-04-20T15:03:33.907248Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import accuracy_score, classification_report\n",
    "from sklearn import tree\n",
    "import matplotlib.pyplot as plt"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:39.241700Z",
     "start_time": "2025-04-20T15:03:39.217356Z"
    }
   },
   "cell_type": "code",
   "source": [
    "iris = load_iris()\n",
    "X = iris.data\n",
    "y = iris.target\n",
    "print(\"特征名称：\", iris.feature_names)\n",
    "print(\"类别名称：\", iris.target_names)"
   ],
   "id": "317f7edd18e0bc4b",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "特征名称： ['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']\n",
      "类别名称： ['setosa' 'versicolor' 'virginica']\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:39.320823Z",
     "start_time": "2025-04-20T15:03:39.315164Z"
    }
   },
   "cell_type": "code",
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.3, random_state=42\n",
    ")"
   ],
   "id": "3d3426f088c2efca",
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.080337Z",
     "start_time": "2025-04-20T15:03:40.067474Z"
    }
   },
   "cell_type": "code",
   "source": [
    "clf = DecisionTreeClassifier(criterion='gini', max_depth=3, random_state=42)\n",
    "clf.fit(X_train, y_train)"
   ],
   "id": "d7d4f8a79728a15e",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(max_depth=3, random_state=42)"
      ],
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=3, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=3, random_state=42)</pre></div> </div></div></div></div>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.188586Z",
     "start_time": "2025-04-20T15:03:40.177639Z"
    }
   },
   "cell_type": "code",
   "source": [
    "y_pred = clf.predict(X_test)\n",
    "print(\"准确率：\", accuracy_score(y_test, y_pred))\n",
    "print(\"分类报告：\\n\", classification_report(y_test, y_pred, target_names=iris.target_names))"
   ],
   "id": "18fd0be58ba4b7f4",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "准确率： 1.0\n",
      "分类报告：\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "      setosa       1.00      1.00      1.00        19\n",
      "  versicolor       1.00      1.00      1.00        13\n",
      "   virginica       1.00      1.00      1.00        13\n",
      "\n",
      "    accuracy                           1.00        45\n",
      "   macro avg       1.00      1.00      1.00        45\n",
      "weighted avg       1.00      1.00      1.00        45\n",
      "\n"
     ]
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.292575Z",
     "start_time": "2025-04-20T15:03:40.288466Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import matplotlib\n",
    "matplotlib.rcParams['font.family'] = 'SimHei'"
   ],
   "id": "34f8b239e9b8c5e2",
   "outputs": [],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.834344Z",
     "start_time": "2025-04-20T15:03:40.316101Z"
    }
   },
   "cell_type": "code",
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "tree.plot_tree(clf, filled=True, feature_names=iris.feature_names, class_names=iris.target_names)\n",
    "plt.title(\"决策树可视化\")\n",
    "plt.show()"
   ],
   "id": "949477eb7a6eda12",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.852295Z",
     "start_time": "2025-04-20T15:03:40.850060Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "76a18d831d89d99b",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.872008Z",
     "start_time": "2025-04-20T15:03:40.869463Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "dbb5bec29e684313",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T15:03:40.887659Z",
     "start_time": "2025-04-20T15:03:40.885158Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "68f3e51604fb0de2",
   "outputs": [],
   "execution_count": null
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
